This research demonstrates enhanced learning outcomes in linear algebra, leveraging AI and intelligent tutoring systems while addressing data privacy and educator adaptation challenges.
Key Points
AI-driven teaching models improve students' comprehension and self-directed learning abilities.
Key strategies include intelligent teaching platforms and personalized resource recommendations to optimize learning.
Addressing challenges in data privacy and teacher training is crucial for successful AI implementation in education.
Future developments will enhance AI's role in educational innovation through multimodal interactions and interdisciplinary approaches.